d2e6192eb2
The SDXL trainer drew min(train_batch_size, len(pairs)) indices, so a dataset with fewer images than the batch trained at a smaller effective batch than configured while the scheduler and samples-per-second still assumed the full batch. The shared PermutationBatchSampler already refills across permutation cycles to return exactly k indices, and the DiT trainer calls it with the full batch size, so drop the clamp and pass train_batch_size through for parity and to honor the configured batch. |
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| .. | ||
| backend | ||
| frontend | ||
| src-tauri | ||
| __init__.py | ||
| install_llama_prebuilt.py | ||
| install_node_prebuilt.py | ||
| install_python_stack.py | ||
| install_sd_cpp_prebuilt.py | ||
| LICENSE.AGPL-3.0 | ||
| node_prebuilt_pins.json | ||
| package-lock.json | ||
| package.json | ||
| setup.bat | ||
| setup.ps1 | ||
| setup.sh | ||
| Unsloth_Studio_Colab.ipynb | ||